Alex Li

I am an Associate Professor of Robotics and AI at University College London, where I lead the Advanced Intelligent Robotics Lab. I received my Ph.D. in Robotics from the Italian Institute of Technology and the University of Genova, and previously held faculty and research positions at the University of Edinburgh and Italian Institute of Technology.

My research focuses on Embodied AI, robot learning, and intelligent control, with the overarching goal of enabling robots to perform skilful manipulation and locomotion in real-world domains.

I am particularly interested in combining deep reinforcement learning, vision-language models, and multi-agent systems to develop autonomous systems with human-level adaptability and beyond.

My work has been published in Science Robotics and Nature Machine Intelligence, and has been featured by BBC News, Wired, New Scientist, and TechXplore. I also serve as an Associate Editor for IEEE journals and actively engage in UK's national robotics initiatives.

Google Scholar / YoTube / LinkedIn /

Your Name

News🚀

Projects ✍️

HARMONY: Enhancing Healthcare with Assistive Robotic Mobile Manipulation

Autonomous Mobile Manipulation: A mobile YuMi robot navigates and operates safely in clinical environments, transporting medical storage boxes and retrieving sample containers.

We integrate cutting-edge perception, planning, and learning-based control into a holistic solution for robotic mobile manipulation in healthcare.

FAIR-SPACE Hub: UK Centre for Space Robotics and AI

Advancing autonomous manipulation, docking, and assembly in orbital and planetary missions.

As the UK's national centre of research excellence in space robotics and AI, FAIR-SPACE brings together state-of-the-art technologies in autonomy, planning, and control.

WALKMAN DRC: The WALKMAN Robot in DARPA Robotics Challenge

The WALKMAN robot was created by the Italian Institute of Technology (IIT) in Genova, leading the only European team with a fully inhouse built robot to compete in the DARPA Robotics Challenge (DRC) Finals in 2015.

It was 1.85 meters tall advanced dexterous manipulation to compete in the 2015 DARPA Robotics Challenge Finals in performing disaster response.

Selected Publications📖 [All Publications]

show by date

DexSkills: Skill Segmentation Using Haptic Data for Learning Autonomous Long-Horizon Robotic Manipulation Tasks

Xiaofeng Mao, Gabriele Giudici, Claudio Coppola, Kaspar Althoefer, Ildar Farkhatdinov, Zhibin Li†, Lorenzo Jamone

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024

Hierarchical generative modelling for autonomous robots

Hierarchical Generative Modelling for Autonomous Robots

Kai Yuan, Noor Sajid, Karl Friston, Zhibin Li†

Nature Machine Intelligence, Vol 5, 1402–1414, 2023

Hybrid hierarchical learning for complex robotic tasks

RObotic MAnipulation Network (RO-MAN): Hybrid Hierarchical Learning for Solving Complex Sequential Tasks

Eleftherios Triantafyllidis, Fernando Acero, Zhaocheng Liu, Zhibin Li†

Nature Machine Intelligence, Vol 5, 991–1005, 2023

Multi-expert learning for legged locomotion

Multi-Expert Learning of Adaptive Legged Locomotion

Chuanyu Yang, Kai Yuan, Wanming Yu, Qiuguo Zhu, Zhibin Li†

Science Robotics, Vol 5 (49), 2020

Featured by BBC, Wired, and New Scientist

Instance-wise Grasp Synthesis for Robotic Grasping

Xu, Y., Kasaei, M., Kasaei, H., & Li, Z.

IEEE International Conference on Robotics and Automation (ICRA), 2023, pp. 1744–1750

Learning Adaptive Grasping From Human Demonstrations

Learning Adaptive Grasping From Human Demonstrations

Shuaijun Wang, Wenbin Hu, Lining Sun, Xin Wang, Zhibin Li

IEEE/ASME Transactions on Mechatronics, 2022

Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter

Language-guided Robot Grasping: CLIP-based Referring Grasp Synthesis in Clutter

Tziafas, G., Xu, Y., Goel, A., Kasaei, M., Li, Z, & Kasaei, H.

Proceedings of The 7th Conference on Robot Learning, Vol. 229, 2023, pp. 1450-1466

Sensory feedback in robot locomotion learning

Identifying Important Sensory Feedback for Learning Locomotion Skills

Wanming Yu, Chuanyu Yang, Christopher McGreavy, Eleftherios Triantafyllidis, Guillaume Bellegarda, Milad Shafiee, Auke Jan Ijspeert, Zhibin Li†

Nature Machine Intelligence, Vol 5, 919–932, 2023

Selected Talks 🎙️